Apple CEO Tim Cook says you won't have to give up your privacy to have a great AI assistant Tim Cook on A.I.: "I Don't Think We Have to Throw Our Privacy Away" Now AI is Deliberately Trying to Scare Us, if We Aren't Already Machine Learning Veterans Launch'Element AI' - A Montreal Based Artificial Intelligence Startup ... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Tim Cook on A.I.: "I Don't Think We Have to Throw Our Privacy Away" Now AI is Deliberately Trying to Scare Us, if We Aren't Already TIM COOK: Here's why assistants on phones are better than home speakers like the Echo Machine Learning Veterans Launch'Element AI' - A Montreal Based Artificial Intelligence Startup ... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Scene: It's 2017, and your CEO calls you in. She asks about your market segmentation--you have five personas, based on demographic data. Then she hands you a report from the data scientist. He's identified nine distinct segments, based on purchase intent and customer behavior, for which there is an opportunity to increase margin by better targeting service offerings and marketing messages. "I thought our data scientist was focused on optimizing our media mix," you mention.

A year ago, Danny Lange took over as the head of machine learning at Uber. The ride-sharing company, which launched in 2009, is, essentially, a tech company: It operates entirely through an app. Lange manages a team in San Francisco, and Uber has a smaller team in Seattle. And machine learning has become the underlying foundation for every part of the company. "Machine learning and AI technologies can really solve some very fundamental business problems that are really hard to create hardwired solutions to," said Lange.

Linear regression is a prediction method that is more than 200 years old. Simple linear regression is a great first machine learning algorithm to implement as it requires you to estimate properties from your training dataset, but is simple enough for beginners to understand. In this tutorial, you will discover how to implement the simple linear regression algorithm from scratch in Python. How To Implement Simple Linear Regression From Scratch With Python Photo by Kamyar Adl, some rights reserved. This section is divided into two parts, a description of the simple linear regression technique and a description of the dataset to which we will later apply it.

Microsoft just released the open-source licensed beta release of the Microsoft Cognitive Toolkit on Github. This announcement represents a shift in Microsoft's customer focus from research to implementation. It is an update to the Computational Network Toolkit (CNTK). The toolkit is a supervised machine learning system in the same category of other open-source projects such as Tensorflow, Caffe and Torch. Microsoft is one of the leading investors in and contributors to the open machine learning software and research community.

The Slackbot is getting a "cognitive" makeover. IBM Watson, Big Blue's big gamble on machine learning, is preparing to perform brain surgery. IBM IBM has partnered with Slack, the fast-growing workplace messaging app, to power the next iteration of Slackbot, Slack's flagship virtual assistant, the companies said Wednesday. Slack said it plans to adopt "Watson Conversation," a month-old tool that helps bots interact through natural language, for its own assistant. In addition, IBM and Slack are planning to develop new artificially intelligent chat features, developer tools, and a brand new bot aimed at assisting I.T. teams and administrators. Developers building applications on top of Slack will be able to draw on various Watson-powered tools, including sentiment analysis, which parses speech to infer emotion, and speech plug-ins, which translate text to spoken language, the company said.

Being able to commute back and forth to work while sleeping, eating, playing Trivia Crack or catching up on your favorite blogs in Feedly is a concept that is equally appealing and seemingly far-off and too futuristic to actually happen. When Google announced their autonomous car project in 2008, visions of Minority Report began to swirl in our heads while we wondered about the possibilities of a car that really had no need for us to do anything other than turn it on. This same car wouldn't have to worry about accidents, distraction, or driving under the influence while it made thousands – or even millions – of split-second calculations in order to keep your safe. You see, as it turns out, humans are remarkably bad at driving. "People are not great at driving -- 30,000 people die in car accidents each year (in the United States). Machines can be much better than humans when it comes to driving; they don't drink or text and can think faster."

Gartner states that its predictions "examine three fundamental effects of continued digital innovation", comprising experience and engagement, business innovation and secondary effects resulting from increased digital capabilities. By 2020, algorithms will positively alter the behaviour of more than 1 billion global workers: algorithms can positively alter human behaviour, augmenting human intelligence with the large collective memory bank containing knowledge that has been socialised and put to the test, with this to help workers "remember" anything or be informed of just-in-time knowledge they have never even experienced, leaving them to objectively complete the task at hand, while also better appreciating life as it unveils. Through 2020, IoT will increase data centre storage demand by less than 3 per cent: of the roughly 900 exabytes of data centre hard-disk drive and solid-state drive capacity forecast to ship in 2020, IoT discrete sensor storage will represent only 0.4 per cent, with storage from multimedia sensors consuming another 2 per cent, indicating IoT can scale and deliver important data-driven business value and insight while remaining manageable from a storage infrastructure standpoint. By 2020, 40 per cent of employees can cut their healthcare costs by wearing a fitness tracker: companies will increasingly appoint fitness program managers, working closely with human resource leaders, including fitness trackers in wellness programs as part of a broader employee engagement initiative.

The age of artificial intelligence is upon us. Advanced AI capabilities are already bringing transformational benefits to organizations, and one significant area where AI is making a difference is in the marketing realm. In fact, according to a new study, 64% of early adopters with advanced AI capabilities are applying it to marketing use cases. They're turning to AI to help find and engage new customers, and to analyze the growing volume and velocity of data critical to targeting their audiences. AI solutions help speed up discovery and synthesis of information and augment decision making to reach, engage and maintain valuable customer relationships.